A high-precision measurement method for large-area foundation settlement combining point and surface

Abstract

The present invention provides a high-precision measurement method for large-area foundation settlement combining point and surface, which relates to the technical field of foundation measurement methods. The surface settlement DEM of large-area soft foundation treatment is obtained by using UAV aerial survey. Then, based on the surface settlement measurement data of the surcharge material at a finite number of points and the high-precision sensing measurement data of the foundation surface layer settlement buried before surcharge, through the method of combining point and surface, the least square principle is used to fit and eliminate errors, eliminate the settlement error generated by the self-compression of the surcharge material, and then eliminate the large-area settlement measurement accuracy error, so as to obtain a DEM of the large-area foundation surface layer settlement with higher precision.

Description

Technical Field

[0001] The present invention relates to the technical field of foundation measurement methods, and more particularly to a high-precision measurement method for large-area foundation settlement that combines point and surface Background Art

[0002] In soft foundation treatment projects, it is essential to monitor the settlement of the foundation. Conducting settlement monitoring on-site can ensure the safety of construction, prevent the foundation from being damaged and unstable, and at the same time, the monitored data obtained is also an important basis for calculating the current degree of foundation consolidation, determining the preloading time, evaluating the effect of foundation treatment, and predicting the post-construction settlement, providing a reference for the overall construction schedule.

[0003] Although traditional single-point measurement monitoring methods have been developed and matured with high precision, they consume a large amount of manpower and material resources and it is difficult to comprehensively grasp the overall settlement information of the foundation treatment area. Unmanned aerial vehicle (UAV) light detection and ranging (LiDAR) can obtain high-density point cloud data through low-altitude multi-temporal scanning of the target area. Through point cloud filtering, interpolation, and differential calculation, the elevation change of the target area can be obtained. Using UAV-borne LiDAR for settlement monitoring not only has high operation efficiency, low manpower consumption, is not affected by construction and terrain, but also can better grasp the planar characteristics of settlement.

[0004] At present, UAV-borne LiDAR has been widely used in fields such as topographic surveying and mapping, power line inspection, land resource planning and renovation, and surface subsidence monitoring in mining areas. However, there are very few studies and applications on settlement monitoring in soft soil foundation treatment projects. In particular, since UAV-borne LiDAR scans the terrain surface, when the surcharge preloading method is used for foundation treatment, a heavy surcharge material is filled on the foundation. How to eliminate the error of the surcharge material settlement is a key problem to be solved. At the same time, there are problems such as low accuracy in constructing a digital elevation model (DEM) from the data collected by UAVs. Therefore, how to improve the accuracy of the DEM obtained by UAV aerial survey is a hot and difficult problem in using UAVs for planar settlement monitoring. Summary of the Invention

[0005] The present invention discloses a high-precision measurement method for large-area foundation settlement that combines point and surface, aiming to solve the problem of low accuracy in using UAVs for planar settlement monitoring.

[0006] The present invention adopts the following scheme:

[0007] A high-precision measurement method for large-area foundation settlement that combines point and surface, comprising the following steps:

[0008] S1. Plan a flight path through a UAV and obtain three-dimensional point cloud data of the area to be measured through aerial survey;

[0009] S2. Filter the acquired 3D point cloud to obtain the ground point cloud, construct the ground DEM by the irregular triangular network interpolation algorithm from the ground point cloud, and subtract the ground DEMs obtained at different times to obtain the surface settlement DEM;

[0010] S3. Determine the control points within the area to be measured, and obtain the spatial coordinates of each control point by continuously measuring multiple times with the RTK device and taking the average; and measure the surface settlement of the foundation at the positions of the control points;

[0011] S4. Carry out surcharge preloading treatment, measure the planar coordinates of the surface of the surcharge material at the control points and the elevation values at the positions, and solve by taking the difference of the changes in the elevation values to obtain the surface settlement values of the surface of the surcharge material at these points at different times;

[0012] S5. Subtract the surface settlement value obtained by the settlement plate at the same position from the surface settlement value obtained by the GNSS device at the control points in the same period to obtain the self-settlement amount of the surcharge material in this time period; use the least squares principle to fit the self-settlement amounts of the surcharge material at each control point to obtain the self-settlement DEM of the surcharge material for the entire area to be measured, and subtract the self-settlement DEM of the surcharge material from the surface settlement DEM, so as to construct the surface settlement DEM that eliminates the self-settlement of the surcharge material;

[0013] S6. Determine the uniform correction points within the area to be measured, and obtain the spatial coordinates of each correction point by continuously measuring multiple times with the RTK device and taking the average;

[0014] S7. Obtain the settlement difference of the settlement plate at each correction point during a certain observation period, that is, the surface settlement amount, subtract the surface settlement amount at the corresponding correction point coordinates in the surface settlement DEM that eliminates the self-settlement of the surcharge material constructed in step S5 from the corresponding surface settlement difference obtained by the settlement plate to obtain the surface settlement error value, and use the least squares principle to perform planar fitting on the surface settlement error values and their planar coordinates at all correction points to obtain the surface settlement error correction plane DEM of the entire settlement observation area, and then perform a difference operation by superimposing the surface settlement DEM that eliminates the self-settlement of the surcharge material and the surface settlement error correction plane DEM to reduce the error of the surface settlement DEM caused by UAV aerial survey.

[0015] Further, the specific steps of obtaining the 3D point cloud and the ground point cloud of the area to be measured by UAV aerial survey are as follows:

[0016] S11. Plan the flight route and flight parameters in the area to be measured;

[0017] S12. Fly the UAV, and scan the surface of the area to be measured with the lidar carried by it;

[0018] S13. Export the three-dimensional point cloud of the area to be measured using the DJI Terra UAV point cloud processing software.

[0019] Further, the filtering algorithm of the irregular triangular network adopts the progressive triangular network filtering algorithm. The specific steps to obtain the ground point cloud by filtering the three-dimensional point cloud are as follows:

[0020] S21: Determine the threshold of the filtering model;

[0021] S22: Divide the measurement area into blocks, and select the lowest point of each block in the measurement area as the seed point to construct the initial triangular network;

[0022] S23: If the distance from the point to be determined to the nearest triangular patch and the angle between the line connecting the point to be determined and the nearest triangle vertex and the triangular patch are both less than the set threshold, it is included in the ground points;

[0023] S24: Repeat steps S22 and S23, and the operation ends when no new points are added to the triangular network.

[0024] Further, the specific steps to construct the surface settlement model that eliminates the self-settlement of the surcharge are as follows:

[0025] S31: Determine the control points in the area to be measured, continuously measure the coordinates of the control points multiple times through the RTK device, and take the average value to obtain the actual spatial coordinates of the control points;

[0026] S32: Before starting the surcharge, bury a settlement plate under the foundation surface layer at the position of the established control point. The settlement plate is connected to an automatic settlement sensor to obtain high-precision surface layer settlement;

[0027] S33: After the surcharge preloading foundation treatment reaches full load, drive a settlement rod on the ground surface at the control point position, and install a GNSS device on the settlement rod; the ground surface subsidence drives the settlement rod to generate a downward displacement, so that the GNSS device is also displaced downward. At the same time, the GNSS device measures its own position every hour and uploads the data to realize continuous elevation monitoring of the ground surface. The elevation difference between different time nodes can be used to obtain the ground surface settlement value of the control point during this period;

[0028] S34: For the same control point, the surface settlement value obtained by GNSS during a certain period minus the surface layer settlement value obtained by the settlement plate is the self-settlement value of the surcharge at this control point; thus, the self-settlement of the surcharge at all control points is obtained, and the DEM of the self-settlement of the surcharge for the entire area to be measured is obtained through plane fitting by the least squares principle;

[0029] S35: Superimpose and perform a difference operation on the surface settlement DEM and the self-settlement DEM of the surcharge to obtain the surface layer settlement DEM that eliminates the surcharge settlement on the basis of the surface settlement DEM.

[0030] Further, in step S7, the specific process of using the elevation error value surface model to correct the accuracy of the surface layer settlement DEM is as follows:

[0031] S71: Determine 50m×50m correction points evenly distributed within the area to be measured; continuously measure the coordinates of the correction points multiple times through RTK equipment, and take the average value to obtain the on-site spatial coordinates of the correction points;

[0032] S72: Subtract the measured surface layer settlement value at each correction point by the settlement plate from the surface layer settlement value at the corresponding coordinate of the obtained surface layer settlement DEM to obtain the surface layer settlement error value at the correction point. The surface layer settlement error values of all correction points, combined with their planar coordinates, are used to obtain the surface layer settlement error correction surface DEM of the entire area to be measured through the least squares planar fitting principle;

[0033] S73: Superimpose and subtract the surface layer settlement DEM and the surface layer settlement error correction surface DEM to obtain the final surface layer settlement DEM.

[0034] Further, it also includes step S8: Verification process, and the verification process includes the following steps:

[0035] S81: Determine inspection points within the area to be measured, continuously measure the coordinates of the inspection points multiple times through RTK equipment, and take the average value to obtain the on-site spatial coordinates of the inspection points; for some inspection points, install GNSS equipment by driving settlement rods and bury settlement plates to monitor the self-settlement of the surcharge material; for some inspection points, bury settlement plates under the foundation surface layer to monitor the surface layer settlement of the foundation;

[0036] S82: Export the self-settlement value of the surcharge material at the corresponding inspection point position in the self-settlement DEM of the surcharge material, compare it with the measured self-settlement value of the surcharge material at the inspection point, and analyze the accuracy index to obtain the accuracy of the self-settlement DEM of the surcharge material;

[0037] S83: Export the surface layer settlement value at the corresponding inspection point position in the final surface layer settlement DEM, compare it with the measured surface layer settlement value at the inspection point, and analyze the accuracy index to obtain the settlement monitoring accuracy of the surface layer settlement DEM after error correction.

[0038] Further, in step S2, ground point clouds are obtained based on the filtering algorithm of irregular triangular networks.

[0039] Further, in step S3, automated settlement monitoring sensors are buried before the start of surcharge. The settlement plate is placed under the foundation surface layer at the reference point position, and the settlement plate is connected to the automated settlement monitoring sensor to measure the surface layer settlement of the foundation at the reference point position.

[0040] Furthermore, in step S4, after the graded loading is completed, a settlement rod is set at the control point, and a GNSS device is installed on the settlement rod to determine the plane coordinates of the surface layer of the loading material at the control point and the elevation value of the location by differential GNSS technology.

[0041] Beneficial effects:

[0042] The ground point cloud was obtained by irregular triangulation algorithm, and the surface settlement DEM was constructed. On this basis, the interference of the settlement of the piled material itself in the preloading foundation treatment condition on the foundation settlement monitoring was eliminated. Furthermore, the surface settlement error surface was constructed, and the error of the surface settlement DEM model was reduced by DEM difference calculation, which improved the accuracy of the settlement surface monitoring by UAV. The point-surface combination method realized the rapid, high-precision and low-cost measurement of large-area foundation settlement. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 , point cloud map of the area to be measured obtained by drone aerial survey;

[0044] Figure 2 ,Schematic diagram of point cloud before noise removal;

[0045] Figure 3 ,The effect of point cloud after removing noise;

[0046] Figure 4 , schematic diagram of a partial enlargement of the point cloud before extracting ground points through point cloud filtering;

[0047] Figure 5 , local magnification effect diagram after point cloud filtering extracts ground points;

[0048] Figure 6 , the surface settlement DEM generated by point cloud filtering and interpolation algorithm;

[0049] Figure 7 , spatial layout plan of control points;

[0050] Figure 8 , the spatial layout plan of the correction points;

[0051] Figure 9 , spatial layout plan of checkpoints;

[0052] Figure 10 , schematic diagram of the arrangement of the settling plate, the settling rod and the GNSS equipment in the embodiment;

[0053] Figure 11 , schematic diagram of arrangement of the settling plate in the embodiment;

[0054] Figure 12 , pile loading material self-settlement surface model;

[0055] Figure 13 , the ground surface settlement DEM after precision correction; Specific implementation method

[0056] Combined with Figures 1 to 13 As shown, this embodiment provides a high-precision measurement method for large-area foundation settlement combining point and surface, including the following steps:

[0057] S1. Plan the flight route through the unmanned aerial vehicle, and obtain the three-dimensional point cloud data of the area to be measured through aerial survey;

[0058] S2. Filter the obtained three-dimensional point cloud through a filtering algorithm based on the irregular triangular network to obtain the ground point cloud, construct the ground DEM by the irregular triangular network interpolation algorithm from the ground point cloud, and subtract the ground DEMs obtained in different periods to obtain the surface settlement DEM;

[0059] S3. Determine the control points within the area to be measured, and obtain the spatial coordinates of each control point by continuously measuring multiple times with the RTK device and taking the average value; Before starting the surcharge, bury the automatic settlement monitoring sensor, place the settlement plate under the ground surface layer at the position of the control point, connect the settlement plate to the automatic settlement monitoring sensor, and measure the surface settlement of the foundation at the position of the control point;

[0060] S4. Carry out the surcharge preloading treatment. After the staged surcharge is completed, drive the settlement rod at the control point, install the GNSS device on it, measure the plane coordinates of the surface of the surcharge material at the control point and the elevation value of the location where it is located through the differential GNSS technology, and solve by taking the difference of the changes in the elevation value to obtain the surface settlement value of the surface of the surcharge material at this point in different periods;

[0061] S5. Subtract the surface settlement value obtained by the GNSS device at the control point in the same period from the surface settlement value measured by the settlement plate at the same position to obtain the self-settlement amount of the surcharge material during this time period; Use the least square principle to fit the self-settlement amounts of the surcharge materials at each control point to obtain the self-settlement DEM of the entire surface to be measured, and subtract the self-settlement DEM of the surcharge material from the surface settlement DEM, so as to construct the surface settlement DEM that eliminates the self-settlement of the surcharge material;

[0062] S6. Determine the uniform correction points within the range of the area to be measured (for example, 50m×50m), and obtain the spatial coordinates of each correction point by continuously measuring multiple times with the RTK device and taking the average value;

[0063] S7. Obtain the settlement difference of the settlement plate at each correction point within a certain observation period, that is, the surface layer settlement amount. Subtract the surface layer settlement amount corresponding to the correction point coordinates in the surface layer settlement DEM that eliminates the self-settlement of the surcharge material constructed in step S5 from the corresponding surface layer settlement difference obtained by the settlement plate to obtain the surface layer settlement error value. Use the least squares principle to perform plane fitting on the surface layer settlement error values and their plane coordinates at all correction points to obtain the surface layer settlement error correction plane DEM of the entire settlement observation surface. Then, superimpose and perform a difference operation on the surface layer settlement DEM that eliminates the self-settlement of the surcharge material and the surface layer settlement error correction plane DEM to reduce the error of the surface layer settlement DEM caused by UAV aerial survey, thereby improving the accuracy of the settlement surface monitoring.

[0064] In the above method, first use UAV aerial survey of the area to be measured and the filtering algorithm to obtain the surface DEMs of different periods, and then subtract the surface DEMs of the area to be measured obtained in different periods to obtain the surface settlement DEM. However, this surface settlement DEM does not eliminate the influence of the self-settlement of the surcharge material on the surface layer settlement DEM in the area to be measured. Therefore, it is necessary to eliminate the settlement value caused by the self-settlement of the surcharge material. For this purpose, select a certain density of control points in the area to be measured, and measure the plane coordinates and elevation values of the surface of the control points through differential GNSS technology. Since the surface settlement amount of the control points obtained by the GNSS device includes the foundation surface layer settlement amount and the self-settlement amount of the surcharge material piled on it, it is necessary to subtract the surface layer settlement amount at the same position from the surface settlement amount obtained by the GNSS device in the same period to obtain the self-settlement amount of the surcharge material in this period. Fit the self-settlement amounts of the surcharge material at multiple control points into the self-settlement DEM of the surcharge material. Subtract the surface settlement DEM from the self-settlement DEM of the surcharge material to eliminate the error caused by the self-settlement of the surcharge material and obtain the surface layer settlement DEM.

[0065] Meanwhile, by burying settlement plates under the foundation surface layer before surcharge loading, the surface layer settlement of the foundation at the position of the control points is measured; the accuracy of the surface layer settlement data obtained by the settlement plates in cooperation with the automatic settlement monitoring sensors is better than that obtained by UAV aerial survey. If only the settlement plates are buried for surface layer settlement monitoring, it is impossible to overall grasp the differential settlement of the foundation treatment area in terms of area. Therefore, UAV aerial survey can be used to construct the surface layer settlement DEM. In order to improve the accuracy of the surface layer settlement DEM obtained by UAV aerial survey, error correction is required. In this embodiment, higher-precision foundation surface layer settlement values are obtained by burying settlement plates. The displacement of the settlement plates at different time points based on the change amount of the initial displacement is the surface layer settlement amount of the correction points during this time period; according to the correction point plane coordinates (x, y), the surface layer settlement values at the corresponding positions of the foundation surface layer settlement DEM are derived. By taking the difference between the surface layer settlement values at the correction points and the surface layer settlement values at the corresponding coordinates of the surface layer settlement DEM, the surface layer settlement error values at the correction points are obtained; then, the surface layer settlement error values obtained at all correction points are combined with their plane coordinates to fit a surface layer settlement error correction surface DEM. Finally, the surface layer settlement DEM and the error correction surface DEM are superimposed and subtracted, and the surface layer settlement DEM with reduced error and improved accuracy is obtained. The surface layer settlement DEM here is the settlement surface obtained after eliminating the influence of the self-settlement of the surcharge material from the surface settlement DEM.

[0066] In the solution of this embodiment, during the process of eliminating the self-error of the surcharge material and correcting the error, the relative height difference is used instead of the absolute elevation difference. Therefore, this solution can be applied in various situations and is not affected by factors such as altitude.

[0067] In this embodiment, the specific steps for obtaining the three-dimensional point cloud of the area to be measured by UAV aerial survey are as follows:

[0068] S11. Plan the flight route and flight parameters in the area to be measured;

[0069] The UAV flight route design mainly includes: flight altitude, flight direction, and overlap rate. The process is as follows:

[0070] Determine the flight altitude: According to the formula

[0071] ; (1)

[0072] The flight altitude H corresponding to a certain ground resolution is calculated. The unit of H is meters; in formula (1), GSD is the ground resolution, the unit is meters; f is the focal length of the camera lens, the unit is millimeters; a is the pixel size of the camera, the unit is micrometers;

[0073] Overlap rate determination: It is determined according to the topographic and geomorphic features of the study area. The recommended flight line overlap rate is 80% and the side overlap rate is 70%, which is applicable to most scenarios. For areas with large topographic fluctuations, when the overlap degree difference between the lowest and highest points of the terrain is too large, in order to ensure the overlap degree at the highest point, the overlap rate can be appropriately increased. For areas with small topographic fluctuations such as plain areas, the overlap rate can be appropriately reduced to improve the aerial survey efficiency, but it is necessary to ensure that the flight line overlap rate is not less than 65% and the side overlap rate is not less than 60%;

[0074] Flight line determination: It is determined according to the shape of the study area along the main axis direction of the study area;

[0075] The flight parameters mainly include: flight speed, altitude;

[0076] The point cloud acquisition parameters mainly include the point cloud density. Multiple aerial surveys are carried out at different time points. The unmanned aerial vehicle automatically flies according to the arranged flight line tasks, and the lidar carried by it scans the ground surface to obtain the point cloud within the area to be measured; then the DJI Terra unmanned aerial vehicle point cloud processing software is used for the preliminary screening of the point cloud, deleting obvious noise points and outliers to obtain the three-dimensional point cloud, exporting the point cloud as the las format, and storing it in the computer.

[0077] The filtering algorithm of the irregular triangular network adopts the progressive triangular network filtering algorithm. The specific steps to obtain the ground point cloud by filtering the three-dimensional point cloud are as follows:

[0078] S21: Determine the threshold of the filtering model; usually in hilly and gully areas, the iteration distance is selected as 1 m and the iteration angle is , in the wind-sand beach area, the iteration distance is 0.5 m and the iteration angle is ;

[0079] S22: Divide the measurement area into blocks, and select the lowest point of each block in the measurement area as the seed point to construct the initial triangular network;

[0080] S23: If the distance from the point to be determined to the nearest triangular patch and the angle between the line connecting the point to be determined and the nearest triangle vertex and the triangular patch are both less than the set threshold, it is included in the ground points;

[0081] S24: Repeat steps S22 and S23, and the operation ends when no new points are added to the triangular network;

[0082] The specific steps to construct the surface DEM through the ground point cloud and obtain the surface settlement DEM by taking the difference between two-phase surface DEMs are as follows:

[0083] Select the irregular triangular network interpolation algorithm (TIN) for the ground point cloud to generate the DEM model. Overlap the two-phase DEM models obtained at different times, and use the raster calculator tool to perform the difference operation to obtain the surface settlement DEM during this time period.

[0084] The specific steps for constructing the surface settlement model to eliminate the self-settlement of the surcharge are as follows:

[0085] S31: Determine a certain density of control points within the area to be measured. Continuously measure the coordinates of the control points multiple times through an RTK device, and take the average value to obtain the on-site three-dimensional coordinates of the control points;

[0086] S32: Before starting the surcharge, bury a settlement plate under the foundation surface layer at the position of the established control points. The settlement plate is connected to an automated settlement monitoring sensor to obtain the settlement of the foundation surface layer;

[0087] S33: After the surcharge preloading foundation treatment reaches full load, drive a settlement rod on the ground surface at the position of the control points. A fixed ring is sleeved outside the settlement rod, and this fixed ring is stabilized on the ground through a tripod to limit the lateral tilt of the settlement rod in the horizontal direction. Install a GNSS device on the settlement rod; the ground surface subsides, driving the settlement rod to displace downward, so that the GNSS device also displaces downward. At the same time, the GNSS device measures its own position every hour and uploads data to continuously monitor the elevation value of the ground surface. The difference between the elevation values at different time nodes can be used to obtain the settlement value of the control point during this period; the GNSS device can continuously measure the three-dimensional space coordinates of the control point according to the set measurement time interval and upload them to the receiver. Take the average value of the three-dimensional space coordinates of the control point within the target time period to obtain the on-site three-dimensional coordinates of the control point. The change amount of its Z coordinate along the gravity direction reflects the settlement amount of the ground surface. The difference between the elevation values of the control point at different time nodes can be used to obtain the surface settlement value of the control point during this period. Subtract the settlement value of the foundation surface layer measured by the settlement plate from this surface settlement value to obtain the self-settlement value of the surcharge;

[0088] S34: For the same control point, the self-settlement value of the surcharge at this control point is the surface settlement value minus the surface layer settlement value during a certain time period; thus, the self-settlement of the surcharge at all control points is obtained, and through the least squares principle for plane fitting, the DEM of the self-settlement of the surcharge in the entire area to be measured is obtained;

[0089] S35: Use the raster calculator tool to perform a difference operation between the surface settlement DEM and the DEM of the self-settlement of the surcharge to obtain the surface layer settlement DEM that eliminates the self-settlement of the surcharge on the basis of the surface settlement DEM.

[0090] In step S7, the specific process of precision correction of the foundation surface layer settlement DEM using the elevation error value surface model is as follows:

[0091] S71: Determine a certain density of correction points with uniform distribution within the area to be measured; continuously measure the coordinates of the control points multiple times through an RTK device, and take the average value to obtain the on-site three-dimensional coordinates of the correction points;

[0092] S72: The settlement measurement value of the settlement plate buried at the correction point is subtracted from the foundation surface settlement value at the corresponding coordinate of the surface settlement DEM, and the surface settlement error value at this correction point is obtained. The settlement error values at all correction points are used to obtain the surface settlement error correction plane DEM of the entire area to be measured through the least squares plane fitting principle. Specifically, the RTK device is used to measure the three-dimensional space coordinates of each correction point multiple times, and the average value is taken to obtain its three-dimensional coordinates. The purpose is to obtain the plane coordinates (x, y) in the three-dimensional coordinates to determine the plane position of the correction point. The displacement of the settlement plate at different time points is subtracted based on the initial displacement, and the settlement of the foundation surface at the correction point during this time period can be obtained. According to the plane coordinates (x, y) of the correction point, the foundation surface settlement value at the corresponding position of the foundation settlement DEM is derived, and the surface settlement error value at the correction point is obtained by subtracting the foundation surface settlement value at the corresponding coordinate of the foundation surface settlement DEM. Thus, the foundation surface settlement error values at all correction points within the area to be measured are obtained.

[0093] S73: The raster calculator tool is used to superimpose and subtract the foundation surface settlement DEM and the surface settlement error correction plane DEM to obtain the final foundation surface settlement DEM.

[0094] In an embodiment, it further includes step S8: verification process. The verification process includes the following steps:

[0095] A certain number of inspection points are established within the area to be measured. A part of the inspection points are used for the quality inspection of the self-settlement model of the surcharge material. The self-settlement of the surcharge material is monitored by using the GNSS device and the buried settlement plate: At the inspection point, a settlement plate is buried at the foundation surface under the surcharge material, and the surface settlement of the foundation is monitored based on the automatic settlement monitoring sensor. At the inspection point, a settlement rod is driven into the surface of the surcharge material. A fixing ring is sleeved outside the settlement rod, and this fixing ring is stabilized on the ground through a tripod to limit the lateral tilt of the settlement rod in the horizontal direction. The settlement rod moves as the ground surface subsides; the GNSS device is fixed on the settlement rod and moves as the settlement rod subsides to achieve the settlement monitoring of the ground surface. The surface settlement value at the inspection point is subtracted from the foundation surface settlement value to obtain the self-settlement value of the surcharge material at the inspection point. According to the inspection point coordinates, the settlement value at the corresponding point of the self-settlement DEM model of the surcharge material is derived, and it is compared with the inspection point settlement value to obtain the accuracy of the self-settlement model of the surcharge material and evaluate its reliability.

[0096] Another part of the checkpoint is used for the quality inspection of the foundation surface settlement model after error correction. The surface settlement of the foundation is monitored by burying settlement plates under the foundation surface: settlement plates are buried at the foundation surface under the surcharge material at the checkpoint location, and the surface settlement of the foundation is monitored based on automated settlement monitoring sensors. The settlement of the foundation drives the settlement plate to sink, and the sinking amount of the settlement plate is reflected in the displacement change of the automated settlement monitoring sensor. The change amount of the automated settlement monitoring sensor within a certain time interval is the foundation surface settlement value within this time period; at the checkpoint, multiple measurements are carried out through RTK equipment to obtain the three-dimensional spatial coordinates of the checkpoint, and the average value of the two-dimensional coordinates (x, y) is taken to obtain the plane coordinates of the checkpoint; according to the plane coordinates, the foundation surface settlement DEM after error correction is derived, and the foundation surface settlement value at this point is used to compare with the checkpoint settlement value to determine the accuracy.

[0097] The specific layout plan of the control points, correction points, and checkpoints in the area to be measured is described as follows:

[0098] The optimal layout plan that fully takes into account the monitoring accuracy and the cost performance of construction and raw materials:

[0099] The control points are used for the plane fitting of the self-settlement surface of the surcharge material. The soil properties of the surcharge material are uniform, and no significant differential settlement will occur during its natural consolidation settlement; the control points are evenly distributed around the area to be measured and densely arranged inside;

[0100] The correction points are related to the accuracy correction of the foundation surface DEM and require a greater layout density. They are evenly and densely arranged within the area to be measured, with a distribution interval of 50×50 meters;

[0101] The checkpoints are used to check the accuracy correction effect of the self-settlement surface of the surcharge material and the foundation surface settlement surface, and are evenly arranged with a lower layout density than the control points and correction points.

[0102] In this embodiment, the triangulated irregular network (TIN) filtering algorithm connects discrete point clouds in the structure form of an irregular triangular network. The TIN filtering avoids the errors caused by resampling, and the original elevation information of the laser foot points will not be damaged, thus ensuring the accuracy. The operation process of this algorithm is mainly divided into three steps: First, divide the measurement area into blocks, and select the lowest point of each block in the measurement area as the seed point to construct the initial triangular network. Then, other laser foot points are discriminated according to certain criteria, and the points that meet the discrimination criteria are encrypted into the initial triangular network. The discrimination criteria are: the distance from the point to be determined to the nearest triangular surface and the angle between the line connecting the point to be determined and the nearest triangle vertex and the triangular patch are both less than the set threshold. This filtering process is carried out by iterative encryption of triangles. Finally, repeat this process iteratively, and when no new points are added to the triangular network, the operation ends.

[0103] In this embodiment, a quadratic polynomial plane fitting is performed on the self-settlement of the surcharge material at the control points to obtain the self-settlement surface model of the surcharge material. The specific process is as follows:

[0104] The difference between the surface settlement measured by the GNSS device at the control points and the foundation surface settlement measured by the settlement plate and its planar coordinates (x, y) form a functional relationship:

[0105] △Z = f(x, y), where f(x, y) is a quadratic polynomial function.

[0106] The least squares matrix form corresponding to the settlement fitting plane based on the polynomial is as follows:

[0107] ;

[0108] where ([[]] , ), ([[]] , ),...., ([[]] , ) are the planar coordinates of the control points, △ , △ ,..., △ are the self-settlement values of the surcharge material at the control points; , , ,...,[[]] are the parameters to be solved. By using the solution of the normal equations, the model parameters can be obtained, and thus the self-settlement values of the surcharge material at other points within the area to be measured can be fitted.

[0109] The fitting of the elevation error surface of the correction points is as follows: The basic idea of improving the measurement accuracy in this embodiment is to obtain the error between the foundation surface settlement obtained by the UAV and the surface settlement at the corresponding points through the surface settlement values at a group of elevation correction points within the area to be measured. The error of the surface settlement at the correction points is minimized by the sum of the squares of the errors between the data points and the true error through the fitting method based on the least squares principle, and the error values of the discrete points are fitted into the error value of the surface, that is, the entire error surface is obtained. On the basis of the original foundation surface settlement DEM, subtracting the obtained error surface completes the elimination of the error.

[0110] The difference between the surface settlement at the correction points and the surface settlement at the corresponding points of the foundation surface settlement DEM is the surface settlement error value. Using four-parameter surface fitting, a plane fitting is performed on the surface settlement error values at the correction points to obtain the surface settlement error surface model, and finally, the original surface settlement DEM is corrected according to the surface settlement error to obtain the corrected final surface settlement DEM.

[0111] In a preferred embodiment, the accuracy evaluation index of the checkpoint: Let the surface settlement value of the checkpoint be:

[0112] ;

[0113] The surface settlement value at the corresponding point on the surface settlement model is:

[0114] ;

[0115] (1) The mean relative error MRE refers to the average of the errors between the surface settlement value of the checkpoint and the surface settlement model of the foundation, and the formula for the mean error is:

[0116] ;

[0117] (2) The mean absolute error MAE is an index that can reflect the actual deviation, which refers to the average of the absolute values of the deviations between the model settlement and the checkpoint settlement.

[0118] ;

[0119] (3) The mean square error can evaluate the influence of discrete data on the settlement deviation of the settlement model. The above three evaluation indexes are negatively correlated with the accuracy of the surface settlement DEM, that is, the higher the accuracy of the surface settlement DEM, the smaller the value of this evaluation index.

[0120] ;

[0121] Through the above three error algorithms, inspection and verification can be carried out.

[0122] It should be understood that: The above is only a preferred embodiment of the present invention, and the protection scope of the present invention is not limited to the above embodiments. All technical solutions falling within the idea of the present invention belong to the protection scope of the present invention.

[0123] The introduction of the drawings used in the above embodiments only shows some embodiments of the present invention and should not be regarded as a limitation of the scope. For those of ordinary skill in the art, without creative efforts, other related drawings can also be obtained based on these drawings.

Claims

1. A high-precision measurement method for large-area foundation settlement combining point and surface, characterized in that It includes the following steps: S1. Plan the flight path by using a drone and obtain the three-dimensional point cloud data of the area to be measured through aerial survey; S2. Filter the obtained three-dimensional point cloud to get the ground point cloud, construct the ground DEM by using the irregular triangulation interpolation algorithm from the ground point cloud, and subtract the ground DEMs obtained at different times to get the surface settlement DEM; S3. Determine the control points within the area to be measured, and obtain the spatial coordinates of each control point by continuously measuring multiple times with an RTK device and taking the average; and measure the surface settlement of the foundation at the position of the control points; S4. Carry out surcharge preloading treatment, measure the planar coordinates of the surface of the surcharge material at the control points and the elevation values at the locations, and solve by taking the difference of the changes in the elevation values to obtain the surface settlement values of the surface of the surcharge material at these points at different times; S5. Subtract the surface settlement value measured by the settlement plate at the same position from the surface settlement value obtained by the GNSS device at the control points in the same period to get the self-settlement amount of the surcharge material at this time period; use the least squares principle to fit the self-settlement amounts of the surcharge materials at each control point to obtain the self-settlement DEM of the surcharge material of the entire area to be measured, and subtract the self-settlement DEM of the surcharge material from the surface settlement DEM, so as to construct the surface settlement DEM that eliminates the self-settlement of the surcharge material; S6. Determine the uniform correction points within the area to be measured, and obtain the spatial coordinates of each correction point by continuously measuring multiple times with an RTK device and taking the average; S7. Obtain the settlement difference of the settlement plate at each correction point during a certain observation time period, that is, the surface settlement amount. Subtract the surface settlement amount at the corresponding correction point coordinates in the surface settlement DEM that eliminates the self-settlement of the surcharge material constructed in step S5 from the corresponding surface settlement difference obtained by the settlement plate to obtain the surface settlement error value. Use the least squares principle to perform planar fitting on the surface settlement error values and their planar coordinates at all correction points to obtain the surface settlement error correction surface DEM of the entire settlement observation area. Then, superimpose and perform difference operation on the surface settlement DEM that eliminates the self-settlement of the surcharge material and the surface settlement error correction surface DEM to reduce the error of the surface settlement DEM caused by aerial survey by the drone.

2. The high-precision measurement method for large-area foundation settlement combining point and surface according to claim 1, characterized in that The specific steps to obtain the three-dimensional point cloud and the ground point cloud of the area to be measured through aerial survey by the drone are as follows: S11. Plan the flight path and flight parameters in the area to be measured; S12. Fly the drone, and scan the surface of the area to be measured by the lidar carried by it; S13. Use the DJI Terra drone point cloud processing software to export the three-dimensional point cloud of the area to be measured.

3. The high-precision measurement method for large-area foundation settlement combining point and surface according to claim 1, characterized in that, The filtering algorithm of the irregular triangulation adopts the progressive triangulation filtering algorithm. The specific steps to filter the three-dimensional point cloud to get the ground point cloud are as follows: S21: Determine the threshold of the filtering model; S22: Divide the measurement area into blocks, and select the lowest point of each block in the measurement area as the seed point to construct the initial triangulation; S23: If the distance from the point to be determined to the nearest triangular patch and the angle between the line connecting the point to be determined and the nearest triangle vertex and the triangular patch are both less than the set threshold, then include it in the ground points; S24: Repeat steps S22 and S23, and end the operation when no new points are added to the triangulation.

4. The high-precision measurement method for large-area foundation settlement combining point and surface according to claim 1, characterized in that, The specific steps for constructing a surface settlement model that eliminates the self-settlement of the surcharge are as follows: S31: Determine the control points within the area to be measured. Continuously measure the coordinates of the control points multiple times using RTK equipment, and take the average value to obtain the actual spatial coordinates of the control points. S32: Before starting the surcharge, bury a settlement plate under the foundation surface layer at the position of the determined control points. The settlement plate is connected to an automated settlement sensor to obtain high-precision surface layer settlement. S33: After the surcharge preloading foundation treatment reaches full load, drive a settlement rod on the ground surface at the position of the control points, and install a GNSS device on the settlement rod. The ground surface settlement drives the settlement rod to move downward, causing the GNSS device to move downward together. At the same time, the GNSS device measures its own position every hour and uploads the data to continuously monitor the elevation of the ground surface. The difference between the elevation values at different time nodes can be used to obtain the ground surface settlement value of the control point during this period. S34: For the same control point, the self-settlement value of the surcharge at the control point is obtained by subtracting the surface layer settlement value obtained by the settlement plate from the ground surface settlement value obtained by GNSS during a certain period. Thus, the self-settlement of the surcharge at all control points is obtained, and the self-settlement DEM of the entire area to be measured is obtained through plane fitting based on the least squares principle. S35: Superimpose and perform a difference operation on the ground surface settlement DEM and the self-settlement DEM of the surcharge to obtain a surface layer settlement DEM that eliminates the surcharge settlement on the basis of the ground surface settlement DEM.

5. The high-precision measurement method for large-area foundation settlement combining point and surface according to claim 1, characterized in that, In step S7, the specific process of precision correction of the surface layer settlement DEM using the elevation error value surface model is as follows: S71: Determine evenly distributed 50m×50m correction points within the area to be measured. Continuously measure the coordinates of the correction points multiple times using RTK equipment, and take the average value to obtain the actual spatial coordinates of the correction points. S72: Calculate the difference between the measured surface layer settlement value of the settlement plate at each correction point and the surface layer settlement value at the corresponding coordinate of the obtained surface layer settlement DEM to obtain the surface layer settlement error value at the correction point. The surface layer settlement error values of all correction points, combined with their plane coordinates, are used to obtain the surface layer settlement error correction plane DEM of the entire area to be measured through the least squares plane fitting principle. S73: Superimpose and perform a difference operation on the surface layer settlement DEM and the surface layer settlement error correction plane DEM to obtain the final surface layer settlement DEM.

6. The high-precision measurement method for large-area foundation settlement combining point and surface according to claim 1, characterized in that It also includes step S8: Verification process, and the verification process includes the following steps: S81: Determine the inspection points within the area to be measured. Continuously measure the coordinates of the inspection points multiple times using RTK equipment, and take the average value to obtain the actual spatial coordinates of the inspection points. For some inspection points, install GNSS devices on settlement rods and bury settlement plates to monitor the self-settlement of the surcharge; for some inspection points, bury settlement plates under the foundation surface layer to monitor the surface layer settlement of the foundation. S82: Export the self-settlement value of the surcharge at the corresponding inspection point position in the self-settlement DEM of the surcharge, compare it with the measured self-settlement value of the surcharge at the inspection point, and analyze the precision index to obtain the precision of the self-settlement DEM of the surcharge. S83: Export the surface settlement values at the corresponding inspection point positions in the final surface settlement DEM, compare them with the measured surface settlement values of the inspection points, and analyze the accuracy indicators to obtain the settlement monitoring accuracy of the surface settlement DEM after error correction.

7. The high-precision measurement method for large-area foundation settlement with point-plane combination according to claim 1, characterized in that In step S2, ground point clouds are obtained based on the filtering algorithm of the irregular triangular network.

8. The high-precision measurement method for large-area foundation settlement with point-plane combination according to claim 1, characterized in that In step S3, automated settlement monitoring sensors are buried before the start of surcharge loading. The settlement plate is placed under the foundation surface layer at the control point position, and the settlement plate is connected to the automated settlement monitoring sensor to measure the surface settlement of the foundation at the control point position.

9. The high-precision measurement method for large-area foundation settlement combining point and surface according to claim 1, characterized in that, In step S4, after the staged surcharge loading is completed, settlement rods are driven at the control points, and GNSS devices are installed on them to measure the plane coordinates of the surface of the surcharge material and the elevation values at the locations where they are located through differential GNSS technology.

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